stiffness_random_variable = \
BetaRandomVariable(alpha=3., beta=2., shift=1., scale=2.5)
# Specify spring-mass system:
m = 1.5 # Deterministic mass.
state0 = [0., 0.] # Initial conditions.
t_grid = np.arange(0., 10., 0.1) # Time.
# Initialize model,
model = SpringMass1D(m, state0, t_grid)
# ----------Monte Carlo------------------
# Generate stiffness input samples for Monte Carlo.
num_samples = 5000
stiffness_samples = stiffness_random_variable.draw_random_sample(num_samples)
# Calculate maximum displacement samples using MC simulation.
displacement_samples = np.zeros(num_samples)
for i, stiff in enumerate(stiffness_samples):
displacement_samples[i] = model.get_max_disp(stiff)
# Get Monte carlo solution as a sample-based random variable:
monte_carlo_solution = SampleRandomVector(displacement_samples)
# -------------SROM-----------------------
# Generate SROM for random stiffness.
srom_size = 10
dim = 1
input_srom = SROM(srom_size, dim)
#Random variable for spring stiffness
stiffness_rv = BetaRandomVariable(alpha=3., beta=2., shift=1., scale=2.5)
#Specify spring-mass system:
m = 1.5 #deterministic mass
state0 = [0., 0.] #initial conditions
t_grid = np.arange(0., 10., 0.1) #time
#Initialize model
model = SpringMass_1D(m, state0, t_grid)
#----------Monte Carlo------------------
#Generate stiffness input samples for Monte Carlo
num_samples = 5000
stiffness_samples = stiffness_rv.draw_random_sample(num_samples)
#Calculate maximum displacement samples using MC simulation
disp_samples = np.zeros(num_samples)
for i, stiff in enumerate(stiffness_samples):
disp_samples[i] = model.get_max_disp(stiff)
#Get Monte carlo solution as a sample-based random variable:
mc_solution = SampleRandomVector(disp_samples)
#-------------SROM-----------------------
#generate SROM for random stiffness
sromsize = 10
dim = 1
input_srom = SROM(sromsize, dim)